DataRobot, an enterprise AI development platform, raises $300M

DataRobot's valuation reached $6.3 billion, up from $2.7 billion in November 2020, while it finalizes the acquisition of MLOps startup Algorithmia.

Main Highlights

DataRobot, a startup developing an enterprise AI development platform, announced today the completion of a $300 million series G funding round led by Altimeter Capital and Tiger Global, with participation from Morgan Stanley’s Counterpoint Global, Franklin Templeton, ServiceNow Ventures, and Sutter Hill Ventures. The financing raises DataRobot’s post-money value to $6.3 billion, up from $2.7 billion in November 2020, and comes as the firm closes on the purchase of Seattle-based MLOps startup Algorithmia.

According to CEO Dan Wright, the additional funds would be used to “fuel platform innovation” and “enable DataRobot to offer augmented intelligence” to clients worldwide. DataRobot intends to expand its go-to-market teams, with Sutter Hill assisting the company’s hiring efforts.

“This investment confirms our goal of integrating the best of what humans and robots have to offer to enable predictive insights, better data-driven choices, and unparalleled business value for our customers,” Wright said in a statement. “DataRobot is seeing an increase in the number of clients worldwide using our platform to tackle their most difficult issues at scale.”

The benefits of AI and machine learning might appear ethereal at times, but data indicates that this hasn’t stopped businesses from embracing the technology on a large scale. According to a recent poll conducted by ManageEngine, Zoho’s IT subsidiary, business AI implementation is on the rise. Separately, Gartner discovered that business usage of AI increased 270 percent from 2015 to 2019, with IBM stating that over one-third of respondents to its corporate May 2021 study is using some kind of AI.

However, AI adoption is not always a success. That is why, in 2012, Jeremy Achin, former director of research and modeling at Travelers, and Tom de Godoy, Achin’s former colleague, launched Boston-based DataRobot. The co-founders aimed to create tools that would assist clients in preparing data as well as creating and validating machine learning models, such as classification, advanced regression, time series, and deep learning algorithms.

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DataRobot offers an integrated platform

DataRobot’s platform is available in the cloud, on-premise datacenters, or as a fully managed service. Customers may use it once it is implemented to monitor models via a dashboard and test, run, and update models to improve outcomes. Depending on the demands of the customer, DataRobot may automatically run a “competition” by evaluating hundreds or even thousands of solutions to a problem and producing models with predictions.

In addition, the platform enables data scientists to explore, integrate, and mold a variety of data types and content — from standard tabular data in rows and columns to free-form text, pictures, and geographic data — into assets suited for AI models.

DataRobot boasts triple-digit recurring revenue growth since 2015, with more than 2 billion models generated on the platform to date. Customers include more than a third of the Fortune 50, including Kroger, Nationwide, Lenovo, and PNC, as well as others in banking, health care, insurance, finance, manufacturing, retail, government, sports, and gaming.

The fresh round raises DataRobot’s total funding to more than $1 billion. This places the firm among the best-funded AI companies in the world, trailing competitors such as Determined AI, Explorium, Ople, Domino Data Lab, and Kaskada by hundreds of millions of dollars.


DataRobot claims the acquisition of Algorithmia, announced at the series G closure this morning, would “further cement” its position as a provider of MLOps solutions. DataRobot will integrate Algorithmia’s model-serving tools with its existing monitoring and management capabilities, according to Wright, to provide customers with “the most reliable and cost-effective operational backbone for running any machine learning model,” including deep learning workloads for natural language processing and image processing on CPUs and GPUs.

“Algorithmia’s people and technology substantially enhance our aim to swiftly transition from experimental to applied AI by assisting clients in bringing every model into production with speedy time to value,” Wright said. “We are delighted to welcome the Algorithmia team and extend our leading MLOps solution to companies across the world with world-class, enterprise-grade MLOps infrastructure.”

Diego Oppenheimer and Kenny Daniel created Algorithmia in 2014 to provide a platform for bringing models into production with “enterprise-grade” security and governance. Algorithmia integrates AI, MLOps, and DevOps approaches, developing systems for coordinating clients’ machine learning work from IT, data scientists, and other divisions to coordinate model deployment.

CEO Oppenheimer’s Verdicts

According to CEO Oppenheimer, over 130,000 IT operators, data scientists, and engineers have utilized Algorithmia too far, including Fortune 500 firms such as Merck, Ernst & Young, and Deloitte. Algorithmia has previously secured $38.1 million in venture funding from Norwest Venture Partners, Gradient Ventures, and other investors.

“We recognize that organizations cannot realize the value of their machine learning models unless they can provide those models quickly, consistently, and at scale,” stated Oppenheimer in a news statement. “We’ve known for many years that DataRobot shares this attitude, and we’re excited to combine our commitment to helping clients to flourish in today’s market by providing more models in production, quicker while safeguarding their business.”

DataRobot’s other acquisitions include Nutonian, which developed a service called Eureqa focused on classification, numeric, multi-series, and time series capabilities. More recently, DataRobot nabbed Nexosis and Paxata, companies working to simplify the way developers build AI apps and prep data, as well as Cursor and ParallelM.

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